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• AdamFlow generalizes the Adam optimization method from Euclidean space to probability space for minimizing sliced Wasserstein distance.method 95%
• AdamFlow achieves superior performance in both affine and non-rigid surface registration across various anatomical structures.result 90%
• The method formulates surface meshes as probability measures and surface registration as a distributional optimization problem.method 95%
• The discrepancy between two meshes is measured using an efficient sliced Wasserstein distance with log-linear computational complexity.technical 90%
• Existing local point matching methods for surface registration are computationally efficient but vulnerable to noise and initialization.limitation 85%
• Methods designed for global point set alignment tend to incur a high computational cost.limitation 85%
• The paper provides theoretical analysis of the asymptotic convergence of AdamFlow.technical 90%
• Surface registration plays an important role for anatomical shape analysis in medical imaging.market 95%

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